Brain Computer Interface Systems
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Deep Learning For Eeg-based Brain-computer Interfaces: Representations, Algorithms And Applications
Deep Learning for EEG-Based Brain-Computer Interfaces is an exciting book that describes how emerging deep learning improves the future development of Brain-Computer Interfaces (BCI) in terms of representations, algorithms and applications. BCI bridges humanity's neural world and the physical world by decoding an individuals' brain signals into commands recognizable by computer devices.This book presents a highly comprehensive summary of commonly-used brain signals; a systematic introduction of around 12 subcategories of deep learning models; a mind-expanding summary of 200+ state-of-the-art studies adopting deep learning in BCI areas; an overview of a number of BCI applications and how deep learning contributes, along with 31 public BCI data sets. The authors also introduce a set of novel deep learning algorithms aimed at current BCI challenges such as robust representation learning, cross-scenario classification, and semi-supervised learning. Various real-world deep learning-based BCI applications are proposed and some prototypes are presented. The work contained within proposes effective and efficient models which will provide inspiration for people in academia and industry who work on BCI.Related Link(s)
Brain-Computer Interface Systems
Author: Reza Fazel-Rezai
language: en
Publisher: BoD – Books on Demand
Release Date: 2013-06-05
Brain-Computer Interface (BCI) systems allow communication based on a direct electronic interface which conveys messages and commands directly from the human brain to a computer. In the recent years, attention to this new area of research and the number of publications discussing different paradigms, methods, signal processing algorithms, and applications have been increased dramatically. The objective of this book is to discuss recent progress and future prospects of BCI systems. The topics discussed in this book are: important issues concerning end-users; approaches to interconnect a BCI system with one or more applications; several advanced signal processing methods (i.e., adaptive network fuzzy inference systems, Bayesian sequential learning, fractal features and neural networks, autoregressive models of wavelet bases, hidden Markov models, equivalent current dipole source localization, and independent component analysis); review of hybrid and wireless techniques used in BCI systems; and applications of BCI systems in epilepsy treatment and emotion detections.
New Insights in Brain-Computer Interface Systems
This book, New Insights in Brain-Computer Interface Systems explores the world of BCIs, where cutting-edge technology meets the intricacies of the human brain. From pioneering advancements in neuroprosthetics to innovative applications in cognitive enhancement and rehabilitation, this book offers insight into the latest research and breakthroughs in the field. Written by leading experts, each chapter explores the science behind BCIs, their practical implementations, and the ethical considerations that accompany this rapidly evolving technology. This book is an exploration that spans multiple domains, including healthcare, robotics, virtual reality, biomaterials, education, humanoids, neuro rights, and neurostimulation. Discover how BCIs are transforming patient care and rehabilitation in offering new hope for individuals with neurological conditions. Learn about the groundbreaking use of neural networks in controlling lower limb exoskeletons, enhancing mobility for those with physical limitations. Uncover the applications of BCIs in action observation and motor imagery, reshaping the landscape of rehabilitation and training. Explore sustainable solutions with biodegradable and biohybrid materials crucial for advancing BCI technology. Gain insights into Mindwave applications and their potential to revolutionize learning methodologies. Delve into trust dynamics in human–humanoid interactions and their implications for future collaboration. Engage with the ethical considerations surrounding BCIs and the imperative for safeguarding individual rights. Investigate how frontal lobe stimulation enhances connectivity in Alzheimer’s disease networks, offering new avenues for therapeutic intervention. Whether you are a researcher, practitioner, student, or simply curious about the future of human-computer interaction, this book provides invaluable insights. Are you ready to explore the next frontier of neuroscience and technology?